Lessons Learned from the Marine Management Area Science Program: Insights for Global Conservation Science Programs

Drawing on experiences from the four regions and the overall conduct of the Marine Management Area Science (MMAS) program, this concluding article highlights emergent cross-cutting themes that affected MMAS programs across the regions, summarizes the important conservation outcomes of the MMAS program, and then discusses lessons gained from the actual process of conducting the MMAS program. Based on these insights, particularly the last section, this article concludes with recommendations for other conservation programs, specifically those that are global in scope and are science-based with a specific intent to apply that science to conservation action.     

Testing a Framework for the Efficiency Assessment of Road Safety Measures

Abstract

The objective of this research is to develop and test a framework for efficiency assessment of road safety measures and evaluate its use in decision‐making. An exhaustive review of standard methodologies and practices related to cost‐effectiveness and cost–benefit analyses is carried out for that purpose. Moreover, a number of case studies are performed, concerning the efficiency assessment of various road safety measures in different countries, covering different types of road safety measures (user‐, vehicle‐ or infrastructure‐oriented, policy or enforcement, etc.), ranging from national to local levels of implementation and including both ex ante and ex post evaluations. From the results conclusions are drawn on the efficiency of different road safety measures and the related determinants. Furthermore, the case studies reveal a number of methodology and data issues for which further research is required. The procedures and barriers involved in the use of efficiency assessment techniques at different levels of decision‐making are also highlighted by means of feedback received during and after the various case studies. On the basis of these results, a framework for the promotion, implementation and evaluation of efficiency assessment in road safety decision‐making is proposed. A particular set of recommendations is also presented regarding the treatment of barriers (fundamental, institutional or technical) within the efficiency assessment itself and the related decision‐making process.     

A household-level activity pattern generation model with an application for Southern California

This paper develops and estimates a multiple discrete continuous extreme value model of household activity generation that jointly predicts the activity participation decisions of all individuals in a household by activity purpose and the precise combination of individuals participating. The model is estimated on a sample obtained from the post census regional household travel survey conducted by the South California Association of Governments in the year 2000. A host of household, individual, and residential neighborhood accessibility measures are used as explanatory variables. The results reveal that, in addition to household and individual demographics, the built environment of the home zone also impacts the activity participation levels and durations of households. A validation exercise is undertaken to evaluate the ability of the proposed model to predict participation levels and durations. In addition to providing richness in behavioral detail, the model can be easily embedded in an activity-based microsimulation framework and is computationally efficient as it obviates the need for several hierarchical sub-models typically used in extant activity-based systems to generate activity patterns.     

Influence of oxygenate content on particulate matter emission in gasoline direct injection engine

The relationship between the oxygen content in gasoline and the particulate emission (particle number and weight) was investigated. In order to study the influence of the engine configuration on the particulate emission, four vehicles were tested in which the following systems were installed: Vehicle 1 was equipped with direct injection system which uses central mounted outwardly opening injectors. Vehicle 2 and 3 used direct injection with a side mounted multihole injectors and Vehicle 4 had port fuel injection system. Methyl tert-butyl ether (MTBE) was used as the oxygen booster. The oxygen content in the gasoline was varied from 1 to 3 wt%, which corresponds with an MTBE dosage from 3.55% to 16.11%. This study used fuel that contained the same octane number with a 2% oxygen content without oxygen components, and it was used as the reference fuel in order to distinguish the effect of the oxygen content increases and the octane boosts that result from the MTBE. All vehicle tests were performed on a roller type chassis dynamometer using the New European Driving Cycle (NEDC) and Federal Test Procedure-75 (FTP-75) cycle. The experiment results demonstrate that the oxygen content increases in the gasoline reduced the particulate emission in vehicles with direct injection engines. An equivalent phenomenon was observed in a vehicle with a port fuel injection engine, but its absolute particle number was much smaller than that of the gasoline direct injection engine. The amount of reduction of the particle number in the start (cold) phase of the test cycle was significant compared with the later (hot) phase engine operation. However, particulates were emitted even though the engine was fully warmed up, especially when the engine was highly loaded. Other factors such as fuel economy or other exhaust emissions were not significantly affected by the oxygen content.     

Sheet metal forming simulation considering die deformation

Due to environmental concerns and safety regulations in the automotive industry, the development of strong and lightweight cars has been a hot issue in the last decade. One solution for this purpose would be to use high-strength steel (HSS) and advanced high-strength steel (AHSS). These materials can make the car lighter while maintaining the crash resistance of the vehicle. HSS and AHSS have more resistance force in the die structure compared with conventional steel due to their higher yield and tensile strength and thus, these materials have a greater effect on die deformation during the sheet metal forming process. As a result, die deformation can affect the blank sheet’s drawn pattern, strain, and stress as well as springback. This study presents a sheet metal forming simulation that considers die deformation. The simulation process was compared with conventional simulation methods. Our results indicate that the sheet metal forming simulation with die deformation consideration provides useful information on the die structure as well as formability and springback.     

Surveillance and Poaching on Inshore Reefs of the Great Barrier Reef Marine Park

The Great Barrier Reef (GBR), Australia, is managed under the GBR Marine Park Act (1975) and is seen as a shining example of marine resource management. The principle tool of management is zoning for multiple use. We examined surveillance and illegal fishing around two inshore islands (Magnetic and Orpheus) of the GBR Marine Park in 2000/2001. Both islands are near Townsville, the largest city adjacent to the GBR. Surveillance effort was low, with vessels present on only 16% of days of the year. Measurable but low levels of illegal recreational fishing occurred within no-take zones. Levels decreased with increasing surveillance effort. Thus zoning was not completely successful in protecting fish targeted by fisheries, even within the most highly enforced sections of the Park. The expansion of no-take zones in 2004 from 4.6% to 33.4% of the area of the 358,000 km2 Park represents a considerable challenge for future surveillance and enforcement.     

Real-time vision-based blind spot warning system: Experiments with motorcycles in daytime/nighttime conditions

This paper describes a real-time vision-based blind spot warning system that has been specially designed for motorcycles detection in both daytime and nighttime conditions. Motorcycles are fast moving and small vehicles that frequently remain unseen to other drivers, mainly in the blind-spot area. In fact, although in recent years the number of fatal accidents has decreased overall, motorcycle accidents have increased by 20%. The risks are primarily linked to the inner characteristics of this mode of travel: motorcycles are fast moving vehicles, light, unstable and fragile. These features make the motorcycle detection problem a difficult but challenging task to be solved from the computer vision point of view. In this paper we present a daytime and nighttime vision-based motorcycle and car detection system in the blind spot area using a single camera installed on the side mirror. On the one hand, daytime vehicle detection is carried out using optical flow features and Support Vector Machine-based (SVM) classification. On the other hand, nighttime vehicle detection is based on head lights detection. The proposed system warns the driver about the presence of vehicles in the blind area, including information about the position and the type of vehicle. Extensive experiments have been carried out in 172 minutes of sequences recorded in real traffic scenarios in both daytime and nighttime conditions, in the context of the Valencia MotoGP Grand Prix 2009.     

Climate change projections for variables affecting road networks in Europe

Global climate change will affect road networks during this century. The effects will be different in various parts of the world due to differences in local climate change and in the structure and properties of roads. In this paper, climate change projections are presented for climate variables that are most likely to affect the long-term performance of road networks in Europe. We apply four regional climate simulations up to the year 2100 using two plausible future emission scenarios. The results show that the changing climate will require significant adaptation measures in the near future in order to maintain the operability of the European road network.     

How tube strikes affect macroscopic and link travel times in London

Abstract

The purpose of this study was to investigate the impact of the five strikes on the London Underground (metro) rail system, which occurred in 2009 and 2010, on macroscopic and road link travel times. A consequence of these strikes was an increase in road traffic flows above usual levels. This provides an opportunity to observe the operation of the road network under unusually high flows. The first objective involves the examination of strike effects on inbound (IT) and outbound traffic (OT) within central, inner and outer London. Travel time data obtained from automatic number plate recognition cameras are used within the first part of the analysis. The second more detailed objective was to investigate in spatio-temporal effects on travel times on five road links. Correlation analyses and general linear models are developed using both traffic flow and travel time data. According to the results of the study, the morning IT had approximately twice as much delay as the OT. Central London experienced the highest delays, followed by inner and outer London. As would be expected, the unique full-day strike in 2009 yielded the worst impact on the network with the highest percentage increase in total travel time (60%) occurring during the morning peak in the IT in inner London. The results from the link-level analysis showed statistical significance amongst the examined links indicating heterogeneous effects from one link to another. It was also found that travel time changes may be more effectively captured through time-of-day terms compared to hourly traffic flows.     

Using kinematic driving data to detect sleep apnea treatment adherence

People spend a significant amount of time behind the wheel of a car. Recent advances in data collection facilitate continuously monitoring this behavior. Previous work demonstrates the importance of this data in driving safety but does not extended beyond the driving domain. One potential extension of this data is to identify driver states related to health conditions such as obstructive sleep apnea (OSA). We collected driving data and medication adherence from a sample of 75 OSA patients over 3.5 months. We converted speed and acceleration behaviors to symbols using symbolic aggregate approximation and converted these symbols to pattern frequencies using a sliding window. The resulting frequency data was matched with treatment adherence information. A random forest model was trained on the data and evaluated using a held-aside test dataset. The random forest model detects lapses in treatment adherence. An assessment of variable importance suggests that the important patterns of driving in classification correspond to route decisions and patterns that may be associated with drowsy driving. The success of this approach suggests driving data may be valuable for evaluating new treatments, analyzing side effects of medications, and that the approach may benefit other drowsiness detection algorithms.